solana/core/benches/shredder.rs

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#![feature(test)]
extern crate test;
use rand::seq::SliceRandom;
use raptorq::{Decoder, Encoder};
use solana_ledger::entry::{create_ticks, Entry};
use solana_ledger::shred::{
max_entries_per_n_shred, max_ticks_per_n_shreds, ProcessShredsStats, Shred, Shredder,
MAX_DATA_SHREDS_PER_FEC_BLOCK, RECOMMENDED_FEC_RATE, SHRED_PAYLOAD_SIZE,
SIZE_OF_DATA_SHRED_IGNORED_TAIL, SIZE_OF_DATA_SHRED_PAYLOAD,
};
use solana_perf::test_tx;
use solana_sdk::hash::Hash;
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use solana_sdk::signature::Keypair;
use std::sync::Arc;
use test::Bencher;
fn make_test_entry(txs_per_entry: u64) -> Entry {
Entry {
num_hashes: 100_000,
hash: Hash::default(),
transactions: vec![test_tx::test_tx(); txs_per_entry as usize],
}
}
fn make_large_unchained_entries(txs_per_entry: u64, num_entries: u64) -> Vec<Entry> {
(0..num_entries)
.map(|_| make_test_entry(txs_per_entry))
.collect()
}
fn make_shreds(num_shreds: usize) -> Vec<Shred> {
let shred_size = SIZE_OF_DATA_SHRED_PAYLOAD;
let txs_per_entry = 128;
let num_entries = max_entries_per_n_shred(
&make_test_entry(txs_per_entry),
2 * num_shreds as u64,
Some(shred_size),
);
let entries = make_large_unchained_entries(txs_per_entry, num_entries);
let shredder =
Shredder::new(1, 0, RECOMMENDED_FEC_RATE, Arc::new(Keypair::new()), 0, 0).unwrap();
let data_shreds = shredder
.entries_to_data_shreds(&entries, true, 0, &mut ProcessShredsStats::default())
.0;
assert!(data_shreds.len() >= num_shreds);
data_shreds
}
fn make_concatenated_shreds(num_shreds: usize) -> Vec<u8> {
let data_shreds = make_shreds(num_shreds);
let valid_shred_data_len = (SHRED_PAYLOAD_SIZE - SIZE_OF_DATA_SHRED_IGNORED_TAIL) as usize;
let mut data: Vec<u8> = vec![0; num_shreds * valid_shred_data_len];
for (i, shred) in (data_shreds[0..num_shreds]).iter().enumerate() {
data[i * valid_shred_data_len..(i + 1) * valid_shred_data_len]
.copy_from_slice(&shred.payload[..valid_shred_data_len]);
}
data
}
#[bench]
fn bench_shredder_ticks(bencher: &mut Bencher) {
let kp = Arc::new(Keypair::new());
let shred_size = SIZE_OF_DATA_SHRED_PAYLOAD;
let num_shreds = ((1000 * 1000) + (shred_size - 1)) / shred_size;
// ~1Mb
let num_ticks = max_ticks_per_n_shreds(1, Some(SIZE_OF_DATA_SHRED_PAYLOAD)) * num_shreds as u64;
let entries = create_ticks(num_ticks, 0, Hash::default());
bencher.iter(|| {
let shredder = Shredder::new(1, 0, RECOMMENDED_FEC_RATE, kp.clone(), 0, 0).unwrap();
shredder.entries_to_shreds(&entries, true, 0);
})
}
#[bench]
fn bench_shredder_large_entries(bencher: &mut Bencher) {
let kp = Arc::new(Keypair::new());
let shred_size = SIZE_OF_DATA_SHRED_PAYLOAD;
let num_shreds = ((1000 * 1000) + (shred_size - 1)) / shred_size;
let txs_per_entry = 128;
let num_entries = max_entries_per_n_shred(
&make_test_entry(txs_per_entry),
num_shreds as u64,
Some(shred_size),
);
let entries = make_large_unchained_entries(txs_per_entry, num_entries);
// 1Mb
bencher.iter(|| {
let shredder = Shredder::new(1, 0, RECOMMENDED_FEC_RATE, kp.clone(), 0, 0).unwrap();
shredder.entries_to_shreds(&entries, true, 0);
})
}
#[bench]
fn bench_deshredder(bencher: &mut Bencher) {
let kp = Arc::new(Keypair::new());
let shred_size = SIZE_OF_DATA_SHRED_PAYLOAD;
// ~10Mb
let num_shreds = ((10000 * 1000) + (shred_size - 1)) / shred_size;
let num_ticks = max_ticks_per_n_shreds(1, Some(shred_size)) * num_shreds as u64;
let entries = create_ticks(num_ticks, 0, Hash::default());
let shredder = Shredder::new(1, 0, RECOMMENDED_FEC_RATE, kp, 0, 0).unwrap();
let data_shreds = shredder.entries_to_shreds(&entries, true, 0).0;
bencher.iter(|| {
let raw = &mut Shredder::deshred(&data_shreds).unwrap();
assert_ne!(raw.len(), 0);
})
}
#[bench]
fn bench_deserialize_hdr(bencher: &mut Bencher) {
let data = vec![0; SIZE_OF_DATA_SHRED_PAYLOAD];
let shred = Shred::new_from_data(2, 1, 1, Some(&data), true, true, 0, 0, 1);
bencher.iter(|| {
let payload = shred.payload.clone();
let _ = Shred::new_from_serialized_shred(payload).unwrap();
})
}
#[bench]
fn bench_shredder_coding(bencher: &mut Bencher) {
let symbol_count = MAX_DATA_SHREDS_PER_FEC_BLOCK as usize;
let data_shreds = make_shreds(symbol_count);
bencher.iter(|| {
Shredder::generate_coding_shreds(0, RECOMMENDED_FEC_RATE, &data_shreds[..symbol_count], 0)
.len();
})
}
#[bench]
fn bench_shredder_decoding(bencher: &mut Bencher) {
let symbol_count = MAX_DATA_SHREDS_PER_FEC_BLOCK as usize;
let data_shreds = make_shreds(symbol_count);
let coding_shreds =
Shredder::generate_coding_shreds(0, RECOMMENDED_FEC_RATE, &data_shreds[..symbol_count], 0);
bencher.iter(|| {
Shredder::try_recovery(
coding_shreds[..].to_vec(),
symbol_count,
symbol_count,
0,
0,
1,
)
.unwrap();
})
}
#[bench]
fn bench_shredder_coding_raptorq(bencher: &mut Bencher) {
let symbol_count = MAX_DATA_SHREDS_PER_FEC_BLOCK;
let data = make_concatenated_shreds(symbol_count as usize);
let valid_shred_data_len = (SHRED_PAYLOAD_SIZE - SIZE_OF_DATA_SHRED_IGNORED_TAIL) as usize;
bencher.iter(|| {
let encoder = Encoder::with_defaults(&data, valid_shred_data_len as u16);
encoder.get_encoded_packets(symbol_count);
})
}
#[bench]
fn bench_shredder_decoding_raptorq(bencher: &mut Bencher) {
let symbol_count = MAX_DATA_SHREDS_PER_FEC_BLOCK;
let data = make_concatenated_shreds(symbol_count as usize);
let valid_shred_data_len = (SHRED_PAYLOAD_SIZE - SIZE_OF_DATA_SHRED_IGNORED_TAIL) as usize;
let encoder = Encoder::with_defaults(&data, valid_shred_data_len as u16);
let mut packets = encoder.get_encoded_packets(symbol_count as u32);
packets.shuffle(&mut rand::thread_rng());
// Here we simulate losing 1 less than 50% of the packets randomly
packets.truncate(packets.len() - packets.len() / 2 + 1);
bencher.iter(|| {
let mut decoder = Decoder::new(encoder.get_config());
let mut result = None;
for packet in &packets {
result = decoder.decode(packet.clone());
if result != None {
break;
}
}
assert_eq!(result.unwrap(), data);
})
}